A Large Neighborhood Search heuristic for Supply Chain Network Design

24 pagesMany exact or approximate solution techniques have been used to solve facility location problems and more generally supply chain network design problems. Yet, the Large Neighborhood Search technique (LNS) has almost never been proposed for solving such problems, although it has proven its efficiency and flexibility in solving other complex combinatorial optimization problems. In this paper we propose an LNS framework for solving a four-layer single period multi-product supply chain network design problem involving multimodal transport. Location decisions for intermediate facilities (e.g. plants and distribution centers) are made using the LNS while transportation modes and product flow decisions are determined by a greedy heuristic. As a post-optimization step, we also use linear programming to determine the optimal product flows once the logistics network is fixed. Extensive experiments based on generated instances of different sizes and characteristics show the effectiveness of the method compared with a state-of-the-art solver

A MODELLING FRAMEWORK FOR PROCUREMENT OF A RETAIL DISTRIBUTION SYSTEM WITH ECONOMIC AND ENVIRONMENTAL GOALS

International audienc

A state of the art and a general formulation model of Hub Location-Routing Problems for LTL shipments

National audienceIn many logistic systems for less than truckload (LTL) shipments, transportation of goods from one origin to its destination is made through collection tours to a hub and delivery tours from the same or another hub, while the goods are shipped between two hubs using Full Truckload (FTL) shipments. Therefore, managers need to determine the location of the hubs, the allocation of non-hub nodes, and the optimal collection and delivery routes within the network. This problem, known as the hub location-routing problem (HLRP), is related to both the hub location problem (HLP) and the location-routing problem (LRP). The HLP involves the location of hub facilities concentrating flows in order to take advantage of economies of scale and through which flows are to be routed from origins to destinations. The objective of the HLRP is to minimize the total costs including hub costs, inter-hub transportation costs, and collection/distribution routing costs. Based on the literatures review, the aims of this paper are to analyze the state of the art, propose some generic mathematical models for the HLRP and implement some tests using a MIP solver

A GRASP FOR REAL LIFE INVENTORY ROUTING PROBLEM: APPLICATION TO BULK GAS DISTRIBUTION

International audienc

Supply chain design and distribution planning under supply uncertainty (Application to bulk liquid gas distribution)

La distribution de liquide cryogénique en vrac , ou par camions citernes, est un cas particulier des problèmes d optimisation logistique. Ces problèmes d optimisation de chaines logistiques et/ou de transport sont habituellement traités sous l hypothèse que les données sont connues à l avance et certaines. Or, la majorité des problèmes d optimisation industriels se placent dans un contexte incertain. Mes travaux de recherche s intéressent aussi bien aux méthodes d optimisation robuste que stochastiques.Mes travaux portent sur deux problèmes distincts. Le premier est un problème de tournées de véhicules avec gestion des stocks. Je propose une méthodologie basée sur les méthodes d optimisation robuste, représentant les pannes par des scénarios. Je montre qu il est possible de trouver des solutions qui réduisent de manière significative l impact des pannes d usine sur la distribution. Je montre aussi comment la méthode proposée peut aussi être appliquée à la version déterministe du problème en utilisant la méthode GRASP, et ainsi améliorer significativement les résultats obtenu par l algorithme en place. Le deuxième problème étudié concerne la planification de la production et d affectation les clients. Je modélise ce problème à l aide de la technique d optimisation stochastique avec recours. Le problème maître prend les décisions avant qu une panne ce produise, tandis que les problèmes esclaves optimisent le retour à la normale après la panne. Le but est de minimiser le coût de la chaîne logistique. Les résultats présentés contiennent non seulement la solution optimale au problème stochastique, mais aussi des indicateurs clés de performance. Je montre qu il est possible de trouver des solutions ou les pannes n ont qu un impact mineur.The distribution of liquid gazes (or cryogenic liquids) using bulks and tractors is a particular aspect of a fret distribution supply chain. Traditionally, these optimisation problems are treated under certainty assumptions. However, a large part of real world optimisation problems are subject to significant uncertainties due to noisy, approximated or unknown objective functions, data and/or environment parameters. In this research we investigate both robust and stochastic solutions. We study both an inventory routing problem (IRP) and a production planning and customer allocation problem. Thus, we present a robust methodology with an advanced scenario generation methodology. We show that with minimal cost increase, we can significantly reduce the impact of the outage on the supply chain. We also show how the solution generation used in this method can also be applied to the deterministic version of the problem to create an efficient GRASP and significantly improve the results of the existing algorithm. The production planning and customer allocation problem aims at making tactical decisions over a longer time horizon. We propose a single-period, two-stage stochastic model, where the first stage decisions represent the initial decisions taken for the entire period, and the second stage representing the recovery decision taken after an outage. We aim at making a tool that can be used both for decision making and supply chain analysis. Therefore, we not only present the optimized solution, but also key performance indicators. We show on multiple real-life test cases that it isoften possible to find solutions where a plant outage has only a minimal impact.NANTES-ENS Mines (441092314) / SudocSudocFranceF

A memetic algorithm for the hub location-routing problem

International audienceIn many logistic systems for less than truckload (LTL) shipments, transportation of goods is made through collection/delivery tours to/from a hub. The design of such a logistic network corresponds to the Hub Location Routing Problem (HLRP). HLRP consists in locating hub facilities concentrating flows in order to take advantage of economies of scale and through which flows are to be routed from origins to destinations, and considers also both collection and distribution routes. We present a generic MIP formulation of this problem and a solution method based on a genetic algorithm improved by some local searches. Computational experiments are presented

An Inventory Pick-up and Delivery Problem in the Reverse Logistics Context: Optimization using a GRASP and hybrid approach

International audienceWe consider the multiperiodic planning and optimization of transport activities (direct and reverse), and inventory management in a two level distribution network. The goal is to satisfy the customers demands while minimizing the routing and storage costs. We use the GRASP and a hybrid approach to solve this problem

PROBLEMES DE TOURNEES AVEC GAINS (ETUDE ET APPLICATION AU TRANSPORT INTER-USINES)

CHATENAY MALABRY-Ecole centrale (920192301) / SudocNANTES-ENS Mines (441092314) / SudocSudocFranceF